---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CR_XLNet_5E
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# CR_XLNet_5E

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6034
- Accuracy: 0.9067

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5384        | 0.33  | 50   | 0.4165          | 0.8533   |
| 0.3633        | 0.66  | 100  | 0.3059          | 0.8867   |
| 0.2642        | 0.99  | 150  | 0.2582          | 0.9267   |
| 0.2626        | 1.32  | 200  | 0.3324          | 0.9      |
| 0.1859        | 1.66  | 250  | 0.4076          | 0.9067   |
| 0.2631        | 1.99  | 300  | 0.4334          | 0.8867   |
| 0.1449        | 2.32  | 350  | 0.4264          | 0.9      |
| 0.1815        | 2.65  | 400  | 0.4334          | 0.8933   |
| 0.1316        | 2.98  | 450  | 0.4436          | 0.9      |
| 0.0725        | 3.31  | 500  | 0.6165          | 0.9      |
| 0.0708        | 3.64  | 550  | 0.6737          | 0.8933   |
| 0.0821        | 3.97  | 600  | 0.5777          | 0.9067   |
| 0.0381        | 4.3   | 650  | 0.6052          | 0.9      |
| 0.0441        | 4.64  | 700  | 0.5853          | 0.9133   |
| 0.0237        | 4.97  | 750  | 0.6034          | 0.9067   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.3.2
- Tokenizers 0.13.1